Presenter(s): Laura Queen
Faculty Mentor(s): Hank Childs & Phil Mote
Oral Session 2 M
The Columbia River has long provided resources as a cultural, economic and ecological agent in the Pacific Northwest. People have congregated along the Columbia’s banks throughout history, from the earliest settlements to contemporary metropoles, but this close proximity poses a serious threat when extreme flooding occurs. Understanding how climate change will affect the future flood risk throughout the Columbia River Basin is imperative for risk mitigation and infrastructural planning. To address this question, we are using an ensemble data set which provides daily streamflow values (1950-2100) for 172 different future projections for 396 locations in the Columbia Basin. To run just one future projection, a modeler must make four choice decisions: the representative concentration pathway (RCP), global climate model (GCM), meteorological downscaling method (MDM), and the hydrological model setup. This ensemble dataset contains 172 projections created by a modeling decision chain containing 2 RCPS, 10 GCMs, 2 MDMs, and 4 setups. With an ensemble dataset produced by multiple hydrologic model parameterizations, we are able to diminish the influence of human-made modeling decisions and find a trend in flood risk change amongst the 172 projections. From the daily time-step streamflow data, we fit probability distributions to extreme events from each water year and estimate flood statistics for floods with 10, 20 and 30 year return periods. From this analysis, we find a substantive increase in flood risk for all outlets sites in the Columbia River Basin and are beginning to study the correlation between sub-basin snow-dominance and increased flood risk.